Multiple graph fusion based on Riemannian geometry for motor imagery classification

In motor imagery-based brain-computer interfaces (BCIs), the spatial covariance features of electroencephalography (EEG) signals that lie on Riemannian manifolds are used to enhance the classification performance of motor imagery BCIs. However, the problem of subject-specific bandpass frequency selection frequently arises in Riemannian manifold-based methods. In this study, we propose a multiple Riemannian graph fusion (MRGF) model to optimize the subject-specific frequency band for a Riemannian manifold. After constructing multiple Riemannian graphs corresponding to multiple bandpass frequency bands, graph embedding based on bilinear mapping and graph fusion based on mutual information were applied to simultaneously extract the spatial and spectral features of the EEG signals from Riemannian graphs. Furthermore, with a support vector machine (SVM) classifier performed on learned features, we obtained an efficient algorithm, which achieves higher classification performance on various datasets, such as BCI competition IIa and in-house BCI datasets. The proposed methods can also be used in other classification problems with sample data in the form of covariance matrices.

H(curl2)-conforming quadrilateral spectral element method for quad-curl problems

In this paper, we propose an [Formula: see text]-conforming quadrilateral spectral element method to solve quad-curl problems. Starting with generalized Jacobi polynomials, we first introduce quasi-orthogonal polynomial systems for vector fields over rectangles. [Formula: see text]-conforming elements over arbitrary convex quadrilaterals are then constructed explicitly in a hierarchical pattern using the contravariant transform together with the bilinear mapping from the reference square onto each quadrilateral. It is worth noting that both the simplest rectangular and quadrilateral spectral elements possess only 8 degrees of freedom on each physical element. In the sequel, we propose our [Formula: see text]-conforming quadrilateral spectral element approximation based on the mixed weak formulation to solve the quad-curl equation and its eigenvalue problem. Numerical results show the effectiveness and efficiency of our method.

Implementation of higher-order velocity mapping between marker particles and grid in the particle-in-cell code XGC

The global total- $f$ gyrokinetic particle-in-cell code XGC, used to study transport in magnetic fusion plasmas or to couple with a core gyrokinetic code while functioning as an edge gyrokinetic code, implements a five-dimensional continuum grid to perform the dissipative operations, such as plasma collisions, or to exchange the particle distribution function information with a core code. To transfer the distribution function between marker particles and a rectangular two-dimensional velocity-space grid, XGC employs a bilinear mapping. The conservation of particle density and momentum is accurate enough in this bilinear operation, but the error in the particle energy conservation can become undesirably large and cause non-negligible numerical heating in a steep edge pedestal. In the present work we update XGC to use a novel mapping technique, based on the calculation of a pseudo-inverse, to exactly preserve moments up to the order of the discretization space. We describe the details of the implementation and we demonstrate the reduced interpolation error for a tokamak test plasma using first- and second-order elements with the pseudo-inverse method and comparing with the bilinear mapping.

Fine-Grained Access Control Scheme Based on Improved Proxy Re-Encryption in Cloud

Cloud storage technology has attracted a considerable number of users owing to its exponential growth. Storing data in the cloud can save the resources of local storage configuration and reduce the cost of local hardware investment. However, the data stored in the cloud is out of the physical control (out of control) of the user. Based on the service characteristics of the cloud environment and the security requirements of user privacy data in the cloud environment, this paper proposes an improved identity proxy re-encryption algorithm based on the advanced encryption standard algorithm. The performance of the algorithm is optimized by reducing the number of bilinear mapping operations, whose calculation takes the longest time in the proxy re-encryption scheme. Only two bilinear mapping operations are required in this scheme. In addition, the encrypted data are tested to different degrees. The experimental results show that this scheme satisfies encryption and decryption performance requirements of the user.

Identity Based Data Sharing and Profile Matching using Probabilistic Key in Cloud

Cloud technology is popular since the utilizations and their information are expanding hugely step by step. It gives usefulness to overseeing data information in a conveyed and pervasive way supporting many platform. Data sharing and security problem are the principle issue to the increasing use of health care, since health information is delicate. However issues, for example, risks of privacy exposure ,versatility in key administration, adaptable access and effective uses denial always been the most significant difficulties for accomplishing goodgrained cryptographically upheld information access control. Right now structure a protected information move and profile coordinating plan with probabilistic open key encryption in correspondence test to diminish the size of open key which helps in decreasing the capacity and furthermore time productive. Our probabilistic open key encryption plot when executed in a bilinear gathering, it can check whether two figure writings are scrambled of a similar message. Strangely, in encryption or decoding system bilinear mapping isn't required in Public Key Encryption conspire except if when individuals need to do in fairness test between two figure messages that might be produced utilizing diverse open keys. Additionally the profile coordinating component dependent on Probabilistic Public Key Encryption with fairness test( PPKEET) causes patient to discover companions in a security saving way with age of trapdoors and structure social connections as indicated by the desire. The security examination and trial results demonstrated that our plan is ensuring the information and giving right medicine in cloud.

Elliptic Curve Digital Signature Algorithm for the Third Party Auditing

Cloud computing usage has been highly increased in past decades, and this has many features to effectively store, organize and process the data. The major concern in the cloud is that security is low and user requires verification process for the data integrity. Third Party Auditing (TPA) technique is applied to verify the integrity of data and various methods has been proposed in TPA for effective performance. The existing methods in TPA has the lower performance in communication overhead and execution time. In this research, Elliptic Curve Digital Signature (ECDS) is proposed to increase the efficiency of the TPA. Bilinear mapping technique is used for verification process without retrieving the data and this helps to reduce the communication overhead. The performance of ECDA is measured and compared with the existing method to analyze the performance.

Certificateless Bilinear Quantum Mutual Exclusive Signcryption for Data Security in Cloud

Signcryption perform both encryption and signature verification simultaneously with minimum computational time and overhead when compared to that of the traditional signature model. Certificateless Sigcryption rectifies issues corresponding to the key escrow problem and hence reducing the key management in the traditional key cryptography in Cloud environment. There has been some Certificateless Signcryption methods proposed, most of which are proved secured using the proxy pairing operations. However, with proxy pairing found to be computationally difficult in understanding and with the discrete operation reducing the advantages gained from smaller key size, data security is said to be compromised. To address this issue, in this work, a method called, Bilinear Quantum Mutual Exclusive Signcryption (BQ-MES) for data security in cloud environment is presented based on quantum principles. The new method inherits the security of bilinear mapping along with quantum, which possesses lower computation complexity than proxy operations, employed in signcrypting data in cloud environment. In the BQ-MES method, only a designated authorized cloud user recovers the data stored in the cloud via cloud service provider by verifying the validity of a signcrypted data. This is performed using Mutually Exclusive Probability model. Experimental works are conducted on the parameters such as computational time, computational overhead and data security rate. By evaluating the performance with related schemes, results show that the data stored in cloud environment is secured using BQ-MES method and computationally efficient.